Refine
Year of publication
Institute
Language
- English (131) (remove)
Document Type
- Conference Proceeding (64)
- Article (59)
- Part of a Book (6)
- Book (2)
Keywords
- Anomaly detection (1)
- Automation (1)
- Autonomous mobile robots (1)
- Benchmark (1)
- Computational modeling (1)
- Control (1)
- Datasets (1)
- GPU (1)
- Heuristic algorithms (1)
- Industry 4.0 (1)
This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.